any2list node + math fixes

__init__.py

@@ -3,7 +3,7 @@ from .custom_nodes.uvr import UVR5Node
 from .custom_nodes.rvc import RVCNode
 from .custom_nodes.loaders import DownloadAudio, LoadAudio, LoadWhisperModelNode, LoadRVCModelNode, LoadHubertModel, LoadPitchExtractionParams
 from .custom_nodes.output import PreviewAudio
-from .custom_nodes.utils import AudioBatchValueNode, MergeImageBatches, MergeLatentBatches, ImageRepeatInterleavedNode, LatentRepeatInterleavedNode, MergeAudioNode, SimpleMathNode, SliceNode
+from .custom_nodes.utils import Any2ListNode, AudioBatchValueNode, MergeImageBatches, MergeLatentBatches, ImageRepeatInterleavedNode, LatentRepeatInterleavedNode, MergeAudioNode, SimpleMathNode, SliceNode, ZipImagesNode
 
 # Set the web directory, any .js file in that directory will be loaded by the frontend as a frontend extension
 WEB_DIRECTORY = "./web"
@@ -29,7 +29,9 @@ NODE_CLASS_MAPPINGS = {
     "DownloadAudio": DownloadAudio,
     "BatchedTranscriptionEncoderNode": BatchedTranscriptionEncoderNode,
     "SimpleMathNode": SimpleMathNode,
-    "SliceNode": SliceNode
+    "SliceNode": SliceNode,
+    "ZipNode": ZipImagesNode,
+    "Any2ListNode": Any2ListNode
 }
 
 # A dictionary that contains the friendly/humanly readable titles for the nodes
@@ -52,5 +54,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "LatentRepeatInterleavedNode": "🌺Latent Repeat Interleaved",
     "BatchedTranscriptionEncoderNode": "🌺Batched CLIP Transcription Encode (Prompt)",
     "SimpleMathNode": "🌺Simple Math Operations",
-    "SliceNode": "🌺Slice Array"
+    "SliceNode": "🌺Slice Array",
+    "ZipNode": "🌺Zip Images",
+    "Any2ListNode": "🌺Any to List"
 }

custom_nodes/stt.py

@@ -264,7 +264,7 @@ class BatchedTranscriptionEncoderNode:
             pooled.append(pc.squeeze())
         
         num_chunks = len(total_chunks)
-        duration_list = list(map(np.round,duration_list))
+        duration_list = np.round(duration_list)
         num_frames = int(np.sum(duration_list))+1
         final_pooled_output = torch.nested.to_padded_tensor(torch.nested.nested_tensor(pooled, dtype=torch.float32),0)
         final_conditioning = torch.nested.to_padded_tensor(torch.nested.nested_tensor(cond, dtype=torch.float32),0)
@@ -278,4 +278,4 @@ class BatchedTranscriptionEncoderNode:
             print(f"{duration_list=}")
             print(f"{num_chunks=}, {max_chunks=}, {num_frames=}")
 
-        return (conditioning, batch_prompt_text, duration_list, num_chunks, num_frames)
+        return (conditioning, batch_prompt_text, list(map(int,duration_list)), num_chunks, num_frames)

custom_nodes/utils.py

@@ -392,6 +392,11 @@ class MergeAudioNode:
         del audios
         audio_name = os.path.basename(audio_path)
         return {"ui": {"preview": [{"filename": audio_name, "type": "temp", "subfolder": "preview", "widgetId": widgetId}]}, "result": (lambda: audio_to_bytes(*merged_audio),)}
+    
+    @classmethod
+    def IS_CHANGED(cls, audio1, audio2, sr="None", merge_type="median", normalize=False, audio3_opt=None, audio4_opt=None):
+        audios = [audio() for audio in [audio1, audio2, audio3_opt, audio4_opt] if audio is not None]
+        return get_hash(sr, merge_type, normalize, *audios)
 
 class SimpleMathNode:
     def __init__(self):
@@ -401,8 +406,8 @@ class SimpleMathNode:
     def INPUT_TYPES(s):
         return {
             "optional": {
-                "n1": ("INT,FLOAT", { "default": 0.0, "step": 0.1 }),
-                "n2": ("INT,FLOAT", { "default": 0.0, "step": 0.1 }),
+                "n1": ("INT,FLOAT", { "default": None, "step": 0.1 }),
+                "n2": ("INT,FLOAT", { "default": None, "step": 0.1 }),
                 "round_up": ("BOOLEAN", {"default": False})
             },
             "required": {
@@ -410,11 +415,11 @@ class SimpleMathNode:
             },
         }
 
-    RETURN_TYPES = ("INT", "FLOAT", )
+    RETURN_TYPES = ("INT", "FLOAT")
     FUNCTION = "do_math"
     CATEGORY = CATEGORY
 
-    def do_math(self, operation, n1 = 0.0, n2 = 0.0, round_up=False):
+    def do_math(self, operation, n1 = None, n2 = None, round_up=False):
         a, b = np.array(n1).flatten(), np.array(n2).flatten()
         if operation=="ADD": number=a+b
         elif operation=="SUBTRACT": number=a-b
@@ -425,7 +430,7 @@ class SimpleMathNode:
         elif operation=="MODULUS": number=a%b
         elif operation=="MIN": number=np.array(list(map(min,zip(a,b))))
         elif operation=="MAX": number=np.array(list(map(max,zip(a,b))))
-        else: number=np.array(n1 or n2).flatten()
+        else: number=a if n1 is not None else b
 
         print(f"{a=} \n{operation=} \n{b=} \n{number=}")
 
@@ -465,4 +470,45 @@ class SliceNode:
 
     def slice(self, array, start=0, end=-1):
         if end==-1: end=len(array)
-        return (array[start:end],)
+        return (array[start:end],)
+
+class ZipImagesNode:
+    def __init__(self):
+        pass
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "images1": ("IMAGE",),
+                "images2": ("IMAGE",),
+            },
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    OUTPUT_IS_LIST = (True, )
+    FUNCTION = "dozip"
+    CATEGORY = CATEGORY
+
+    def dozip(self, images1, images2):
+        return (list(map(torch.stack,zip(images1,images2))),)
+    
+class Any2ListNode:
+    def __init__(self):
+        pass
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "any": (AlwaysEqualProxy("*"),),
+            },
+        }
+
+    RETURN_TYPES = (AlwaysEqualProxy("*"),)
+    OUTPUT_IS_LIST = (True, )
+    FUNCTION = "to"
+    CATEGORY = CATEGORY
+
+    def to(self, any):
+        return (list(any),)

web/js/ui_handlers.js

@@ -309,6 +309,13 @@ app.registerExtension({
                     })
                     break;
 
+                case "Any2ListNode":
+                    chainCallback(nodeType.prototype, "onConnectInput", function (_, inputs) {
+                        this.outputs[0].name = inputs;
+                        this.outputs[0].type = inputs;
+                    })
+                    break;
+
                 default:
                     
                     break